class_docstr: Coreference neural model
code: def _score(self, features, layers):
      for weights, bias in layers:
          # print("features", features.shape)
          features = np.matmul(weights, features) + bias
          if weights.shape[0] > 1:
              features = np.maximum(features, 0)  # ReLU
      return np.sum(features, axis=0)
  
imports: import os
  import spacy
  import numpy
  from neuralcoref.train.utils import PACKAGE_DIRECTORY, SIZE_SINGLE_IN
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Document, MENTION_TYPE, NO_COREF_LIST
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj._score(features, layers) and returns: np